Content adaptive sparse illumination for Fourier ptychography

Fourier Ptychography (FP) is a recently proposed technique for large field of view and high resolution imaging. Specifically, FP captures a set of low resolution images under angularly varying illuminations and stitches them together in Fourier domain. One of FP's main disadvantages is its long capturing process due to the requisite large number of incident illumination angles. In this letter, utilizing the sparsity of natural images in Fourier domain, we propose a highly efficient method termed as AFP, which applies content adaptive sparse illumination for Fourier ptychography by capturing the most informative parts of the scene's spatial spectrum. We validate the effectiveness and efficiency of the reported framework with both simulations and real experiments. Results show that the proposed AFP could shorten the acquisition time of conventional FP by around 30%-60%

Cost Function Statistical Analysis in Double Random Phase Encoding

We examine the Amplitude-Encoding (AE) case of the Double Random Phase Encoding (DRPE) technique. A cost function is the function we use to evaluate an attempted decryption with our original input image. For systems with a relatively small key-space we can evaluate the output of every key to get an overall idea of the spread of these keys in key-space. However for larger systems this is not practical. Based on a normalised root mean squared cost function we wish to identify expressions for the mean and variance of the output (decrypted) intensity for a sample set of keys in a large system (256x256 pixels)

A Cascaded Iterative Fourier Transform Algorithm For Optical Security Applications

A cascaded iterative Fourier transform (CIFT) algorithm is presented for optical security applications. Two phase-masks are designed and located in the input and the Fourier domains of a 4-f correlator respectively, in order to implement the optical encryption or authenticity verification. Compared with previous methods, the proposed algorithm employs an improved searching strategy: modifying the phase-distributions of both masks synchronously as well as enlarging the searching space. Computer simulations show that the algorithm results in much faster convergence and better image quality for the recovered image. Each of these masks is assigned to different person. Therefore, the decrypted image can be obtained only when all these masks are under authorization. This key-assignment strategy may reduce the risk of being intruded.Comment: 18 pages, 4 figures, 2 tables. submitted to Opti

Remote laboratory for digital holographic metrology

Advances in information technology open up the potential of combining optical systems with net based infrastructures, allowing for remote inspection and virtual metrology. In this paper, we report our recent work on building a remote laboratory for digital holographic metrology. We describe the architecture and the techniques involved in setting up the remote controlling metrology system. Further consideration will be given to the integration into an advanced infrastructure for remote experimentation, data storage and publication. Some other important issues such as information security will not be addressed

Lensless complex amplitude demodulation based on deep learning in holographic data storage

To increase the storage capacity in holographic data storage (HDS), the information to be stored is encoded into a complex amplitude. Fast and accurate retrieval of amplitude and phase from the reconstructed beam is necessary during data readout in HDS. In this study, we proposed a complex amplitude demodulation method based on deep learning from a single-shot diffraction intensity image and verified it by a non-interferometric lensless experiment demodulating four-level amplitude and four-level phase. By analyzing the correlation between the diffraction intensity features and the amplitude and phase encoding data pages, the inverse problem was decomposed into two backward operators denoted by two convolutional neural networks (CNNs) to demodulate amplitude and phase respectively. The experimental system is simple, stable, and robust, and it only needs a single diffraction image to realize the direct demodulation of both amplitude and phase. To our investigation, this is the first time in HDS that multilevel complex amplitude demodulation is achieved experimentally from one diffraction intensity image without iterations